apply_along_axis cuts strings

I’m trying to concatenate all elements of a row into a string as follows:

np.apply_along_axis(lambda x: " ".join(map(str, x)), 1, b)

b is

[[111,111,0,0,0], [111,111,111,111,111]]

However, the result of the line is:

['111 111 0 0 0', '111 111 111 1']

It looks like np.apply_along_axis is cutting the second string to be of the same length as the first one. If I put a longer sequence first, the result is correct:

['111 111 111 111 111', '111 111 0 0 0']

So I’m guessing this is a bug?

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Summary 2019-04-30 by @seberg

np.apply_along_axis infers the output dtype from the first pass. Which can be worked around for example but the function returning an array of a correct type.

Actions:

• np.apply_along_axis could/should get a dtype kwarg (or similar, compare also np.vectorize).

[eric-wieser]

I’m assuming that that’s a deliberately contrived example, because you shouldn’t be using apply_along_axis for simple indexing like that.

np.ma.apply_along_axis will work correctly here (for now - see #8511). Another option (crashed until 1.13) is a manual cast to dtype object:

np.apply_along_axis(lambda x: np.array(x[0], object), 1, fnames)

[eric-wieser]

Perhaps we should just add a dtype= argument to apply_along_axis